Title: Auto-Calibration%20and%20Control%20Applied%20to%20Electro-Hydraulic%20Valves
1Auto-Calibration and Control Applied to
Electro-Hydraulic Valves
- A Ph.D. Thesis Proposal
- Presented to the Faculty of the
- George Woodruff School of Mechanical Engineering
- at the Georgia Institute of Technology
- By
- PATRICK OPDENBOSCH
- Committee Members
- Nader Sadegh (Co-Chair, ME)
- Wayne Book (Co-Chair, ME)
- Chris Paredis (ME)
- Bonnie Heck (ECE)
- Roger Yang (HUSCO Intl.)
2PRESENTATION OUTLINE
- INTRODUCTION
- PROBLEM STATEMENT
- OBJECTIVES
- REVIEW OF MOST RELEVANT WORK
- PROPOSED RESEARCH
- PRELIMINARY WORK
- EXPECTED CONTRIBUTIONS
- CONCLUSION
3INTRODUCTION
- CURRENT APPROACH
- Electronic control
- Use of solenoid Valves
- Energy efficient operation
- New electrohydraulic valves
- Conventional hydraulic spool valves are being
replaced by assemblies of 4 independent valves
for metering control
Low Pressure
High Pressure
Spool Valve
Spool piece
Spool motion
Piston
Piston motion
4INTRODUCTION
- CURRENT APPROACH
- Electronic control
- Use of solenoid Valves
- Energy efficient operation
- New electrohydraulic valves
- Conventional hydraulic spool valves are being
replaced by assemblies of 4 independent valves
for metering control
Valve motion
Low Pressure
High Pressure
Piston motion
5INTRODUCTION
- ADVANTAGES
- Independent control
- More degrees of freedom
- More efficient operation
- Simple circuit
- Ease in maintenance
- Distributed system
- No need to customize
Valve motion
Low Pressure
High Pressure
Piston motion
6INTRODUCTION
- METERING MODES
- Standard Extend
- Standard Retract
- High Side Regeneration
- Low Side Regeneration
- DISADVANTAGES
- Nonlinear system
- Complex control
Valve motion
Low Pressure
High Pressure
Piston motion
7INTRODUCTION
Coil Cap
Adjustment Screw
- POPPET ADVANTAGES
- Excellent sealing
- Less faulting
- High resistance to contamination
- High flow to poppet displacement ratios
- Low cost and low maintenance
Modulating Spring
Input Current
Coil
Armature
Pilot Pin
Control Chamber
Armature Bias Spring
U.S. Patents (6,328,275) (6,745,992)
Pressure Compensating Spring
Main Poppet
Forward (Side) Flow
Reverse (Nose) Flow
8INTRODUCTION
Coil Cap
Adjustment Screw
- Electro-Hydraulic Poppet Valve (EHPV)
- Poppet type valve
- Pilot driven
- Solenoid activated
- Internal pressure compensation
- Virtually zero leakage
- Bidirectional
- Low hysteresis
- Low gain initial metering
- PWM current input
Modulating Spring
Input Current
Coil
Armature
Pilot Pin
Control Chamber
Armature Bias Spring
U.S. Patents (6,328,275) (6,745,992)
Pressure Compensating Spring
Main Poppet
Forward (Side) Flow
Reverse (Nose) Flow
9INTRODUCTION
- VALVE CHARACTERIZATION
- Flow Conductance Kv
- or
10INTRODUCTION
- FORWARD MAPPING
- REVERSE MAPPING
Side to nose
Forward Kv at different input currents A
Nose to side
Reverse Kv at different input currents A
11INTRODUCTION
- MOTIVATION
- Need to control valves KV
- Currently done by inversion of the steady-state
input/output characteristics - Requires individual offline calibration
- CHALLENGES
- Online learning of steady state and transient
characteristics - Online estimation of individual Kv.
- ADVANTAGES
- No individual offline calibration
- Design need not be perfect and sufficiently
fast - Maintenance scheduling can be implemented from
monitoring and detecting the deviations from the
normal pattern of behavior.
12PRESENTATION OUTLINE
- INTRODUCTION
- PROBLEM STATEMENT
- OBJECTIVES
- REVIEW OF MOST RELEVANT WORK
- PROPOSED RESEARCH
- PRELIMINARY WORK
- EXPECTED CONTRIBUTIONS
- CONCLUSION
13PROBLEM STATEMENT
- PURPOSE
- Develop a general theoretical framework for
auto-calibration and control of general nonlinear
systems. It is intended to explore the
feasibility of the online learning of the
systems characteristics while improving its
transient and steady state performance without
requiring much a priori knowledge of such system.
- APPLICATION
- This framework is applied to a hydraulic system
composed of electro-hydraulic valves in an effort
to study the applicability of having a
self-calibrated system.
14PROBLEM STATEMENT
- RESEARCH QUESTIONS
- How well can the systems mappings be learned
online while at the same time trying to achieve
good state tracking performance? - How can the tracking error dynamics be maintained
stable while applying learning and estimation on
the system? - How is the learning affected by input saturation
and time-varying dynamics? - In particular for the EHPVs, how well can the
forward and reverse flow mappings be learned? - How can the learned mappings be used for fault
detection?
15PRESENTATION OUTLINE
- INTRODUCTION
- PROBLEM STATEMENT
- OBJECTIVES
- REVIEW OF MOST RELEVANT WORK
- PROPOSED RESEARCH
- PRELIMINARY WORK
- EXPECTED CONTRIBUTIONS
- CONCLUSION
16OBJECTIVES
- THEORETICAL
- Development of a general formulation for control
of nonlinear systems with parametric uncertainty
and time-varying characteristics - Development of a formulation for auto-calibration
of nonlinear systems - Study of learning dynamics online along with
fault diagnosis - Improve Kv control of EHPVs
- EXPERIMENTAL
- Analysis and validation on the effectiveness of
the proposed method - Study of the accuracy of the auto-calibration and
possible drift problems - Development of computationally efficient
algorithms - Development of a nonlinear observer for state
estimation for unmeasurable states
17PRESENTATION OUTLINE
- INTRODUCTION
- PROBLEM STATEMENT
- OBJECTIVES
- REVIEW OF MOST RELEVANT WORK
- PROPOSED RESEARCH
- PRELIMINARY WORK
- EXPECTED CONTRIBUTIONS
- CONCLUSION
18RELEVANT WORK REVIEW
- CONTROL
- Sadegh, N., (1995), A nodal link perceptron
network with applications to control of a
nonholonomic system, IEEE Transactions on Neural
Network, Vol. 6, No. 6, pp. 1516-1523. - Sadegh, N., (1998), A multilayer nodal link
perceptron network with least squares training
algorithm, International Journal of Control, Vol.
70, No. 3, pp. 385-404.
19RELEVANT WORK REVIEW
Sadegh (1995)
- The plant is linearized about a desired
trajectory - A Nodal Link Perceptron Network (NLPN) is
employed in the feedforward loop and trained with
feedback state error - The control scheme needs the plant Jacobian and
controllability matrices obtained offline - Approximations of the Jacobian and
controllability matrices can be used without
loosing closed loop stability.
20RELEVANT WORK REVIEW
Sadegh (1998)
- Nodal Link Perceptron Network (NLPN)
- Functional approximation is achieved by the
scaling of basis functions - The class of basis functions are to be selected
as well as their weights are to be trained so
that the functional approximation error is within
prescribed bounds
21RELEVANT WORK REVIEW
- FLOW OBSERVER
- O'hara, D.E., (1990), Smart valve, in Proc
Winter Annual Meeting of the American Society of
Mechanical Engineers pp. 95-99 - Book, R., (1998), "Programmable electrohydraulic
valve", Ph.D. dissertation, Agricultural
Engineering, University of Illinois at
Urbana-Champaign - Garimella, P. and Yao, B., (2002), Nonlinear
adaptive robust observer for velocity estimation
of hydraulic cylinders using pressure measurement
only, in Proc ASME International Mechanical
Engineering Congress and Exposition pp. 907-916
22RELEVANT WORK REVIEW
- O'hara (1990), Book (1998)
- Concept of Inferred Flow Feedback
- Requires a priori knowledge of the flow
characteristics of the valve via offline
calibration
Squematic Diagram for Programmable Valve
23RELEVANT WORK REVIEW
- Garimella and Yao (2002)
- Velocity observer based on cylinder cap and rod
side pressures - Adaptive robust techniques
- Parametric uncertainty for bulk modulus, load
mass, friction, and load force - Nonlinear model based
- Discontinuous projection mapping
- Adaptation is used when PE conditions are
satisfied
24RELEVANT WORK REVIEW
- Liu and Yao (2005)
- Modeling of valves flow mapping
- Online approach without removal from overall
system - Combination of model based approach,
identification, and NN approximation - Comparison among automated modeling, offline
calibration, and manufacturers calibration
25RELEVANT WORK REVIEW
- HEALTH MONITORING
- Polycarpou and Vemuri (1995)
- Selmic and Lewis (2000)
- Linear modeling techniques
- NN for nonlinear identification
Failure Detection and Accommodation Monitoring
off-nominal behavior
Multimodel Failure Detection
26RELEVANT WORK REVIEW
- HEALTH MONITORING
- Polycarpou, M.M. and Vemuri, A.T., (1995),
Learning methodology for failure detection and
accommodation, IEEE Control Systems, Vol. No.
pp. 16-24. - Selmic, R.R. and Lewis, F.L., (2000),
Identification of nonlinear systems using rbf
neural networks Application to multimodel
failure detection, in Proc XVI International
Conference on "Material flow, machines, and
devices in industry"
27PRESENTATION OUTLINE
- INTRODUCTION
- PROBLEM STATEMENT
- OBJECTIVES
- REVIEW OF MOST RELEVANT WORK
- PROPOSED RESEARCH
- PRELIMINARY WORK
- EXPECTED CONTRIBUTIONS
- CONCLUSION
28PROPOSED RESEARCH
- AUTO-CALIBRATION AND CONTROL
- k 0,1,2 (discrete-time index)
- 0 ui iUMAX, i 1,2,,m
- Set of admissible states
- Set of admissible inputs
29PROPOSED RESEARCH
- AUTO-CALIBRATION AND CONTROL
- k 0,1,2 (discrete-time index)
- 0 ui iUMAX, i 1,2,,m
- The control purpose is to learn the input
sequence uk that forces the states of the
system xk to follow a desired state trajectory
dxk as k?8 - PROPOSED Adaptive approach without requiring
detailed knowledge about the systems model
30PROPOSED RESEARCH
- SQUARE NONLINEAR SYSTEM
- ASSUMPTIONS
- The system is strongly controllable
- The system is strongly observable
- The functions F and H are continuously
differentiable
31PROPOSED RESEARCH
- SQUARE NONLINEAR SYSTEM
- DEFINITIONS
- Jacobian Matrix
- Controllability Matrix
- Observability Matrix
32PROPOSED RESEARCH
- SQUARE NONLINEAR SYSTEM
- CONTROL DESIGN
- Tracking Error
- Error Dynamics
33PROPOSED RESEARCH
- SQUARE NONLINEAR SYSTEM
- CONTROL DESIGN
- Error Dynamics
- Deadbeat Control Law
34PROPOSED RESEARCH
- SQUARE NONLINEAR SYSTEM
- CONTROL DESIGN
- Deadbeat Control Law
- Proposed Control Law
35PROPOSED RESEARCH
Nominal inverse mapping
Estimation of Jacobian and controllability
Feedback correction
inverse mapping correction
36PROPOSED RESEARCH
Nominal inverse mapping
Inverse Mapping Correction
uk
xk
NLPN
PLANT
dxk
Adaptive Proportional Feedback
Jacobian Controllability Estimation
37PROPOSED RESEARCH
- ESTIMATION APPROACHES
- Modified Broyden
38PROPOSED RESEARCH
- ESTIMATION APPROACHES
- Recursive Least Squares
39PROPOSED RESEARCH
For each valve
40PROPOSED RESEARCH
- APPLICATION
- Health Monitoring
- Failures sensor fault, wear of the mating parts,
contamination, break of a component, or component
stiction - Assess valves behavior with respect to the
nominal behavior. - Establish the criteria to declare faulting on the
valves by studying the deviations from the
nominal pattern.
Kv as a Function of Input Current Deviations
from Nominal Patterns
41PROPOSED RESEARCH
- THEORETICAL TASKS
- Work on the convergence properties of the
estimated matrices - Perform analysis about the closed loop stability
of the overall system. - Work on a nonlinear observer for the valves flow
conductances.
- EXPERIMENTAL TASKS
- Hydraulic testbed setup
- Sensor integration, calibration, and filtering
design - Data acquisition and analysis
- Validation of theory
- Compare the performance under learning to that of
fixed input/output mapping
42PRESENTATION OUTLINE
- INTRODUCTION
- PROBLEM STATEMENT
- OBJECTIVES
- REVIEW OF MOST RELEVANT WORK
- PROPOSED RESEARCH
- PRELIMINARY WORK
- EXPECTED CONTRIBUTIONS
- CONCLUSION
43PRELIMINARY WORK
Implemented Nominal Mapping
- NONLINEAR 1ST ORDER DISCRETE TIME SYSTEM
Comparison implemented and true steady state
mapping
44PRELIMINARY WORK
45PRELIMINARY WORK
Closed-loop and open-loop performance
46PRELIMINARY WORK
Estimated Jacobian and Controllability
47PRELIMINARY WORK
- MORE INFORMATION AT
- Opdenbosch, P. and Sadegh, N., (2005), Control of
discrete-time systems via online learning and
estimation, in Proc IEEE/ASME International
Conference on Advanced Intelligent Mechatronics
pp. 975-980
48PRELIMINARY WORK
- Single EHPV learning control being investigated
at Georgia Tech - Controller employs Neural Network in the
feedforward loop with adaptive proportional
feedback - Satisfactory results for single EHPV used for
pressure control
49PRELIMINARY WORK
50PRELIMINARY WORK
- Initial test response, no NLPN learning
Flow Conductance
Estimated Jacobian and Controllability
51PRELIMINARY WORK
- EHPV response with NLPN learning
Flow Conductance
Estimated Jacobian and Controllability
52PRELIMINARY WORK
- MORE INFORMATION AT
- Opdenbosch, P. and Sadegh, N., (2005), Control of
electro-hydraulic poppet valves via online
learning and estimation, in Proc ASME
International Mechanical Engineering Congress and
Exposition, IMECE (Accepted)
53PRESENTATION OUTLINE
- INTRODUCTION
- PROBLEM STATEMENT
- OBJECTIVES
- REVIEW OF MOST RELEVANT WORK
- PROPOSED RESEARCH
- PRELIMINARY WORK
- EXPECTED CONTRIBUTIONS
- CONCLUSION
54EXPECTED CONTRIBUTIONS
- An alternative methodology for control system
design of nonlinear systems with time-varying
characteristics and parametric uncertainty. - A method to estimate and learn the flow
conductance of the valve online. - Guidelines to experimentally use this control
methodology and health monitoring efficiently in
the area of electro-hydraulic control.
55PRESENTATION OUTLINE
- INTRODUCTION
- PROBLEM STATEMENT
- OBJECTIVES
- REVIEW OF MOST RELEVANT WORK
- PROPOSED RESEARCH
- PRELIMINARY WORK
- EXPECTED CONTRIBUTIONS
- CONCLUSION
56CONCLUSIONS
- The proposed control methodology combines
adaptive proportional feedback control with
online corrected feedforward compensation - The input/output mapping of the system can be
easily extracted via a functional approximator on
the feedforward compensation - Extensive knowledge about the dynamics of the
system are not needed a priori for satisfactory
performance - The proposed method is to be employed in a
Wheatstone bridge arrangement of novel
Electro-Hydraulic Poppet Valves seeking a
self-calibrated system